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mzuama/
my_first_qa_model

Name: my_first_qa_model
Availability: InStock

generated_from_trainer

distilbert/distilbert-base-uncased

finetune

apache-2.0

endpoints_compatible

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my_first_qa_model

This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.5850

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	250	2.1675
2.6266	2.0	500	1.6522
2.6266	3.0	750	1.5850

Framework versions

Transformers 4.54.0
Pytorch 2.6.0+cu124
Datasets 4.0.0
Tokenizers 0.21.2

mzuama/my_first_qa_model

my_first_qa_model

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

mzuama/
my_first_qa_model